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Face recognition plays an every important role in security surveillance, secure access and identity authentication. In this paper, we propose a novel face recognition method based on supervised learning. Our method consists in first extracting face feature using a supervised spectral regression, then we use multiple kernel SVM to classify face. Experimental results on Yale B face database and AR face...
Human sounds can be roughly divided into two categories: speech and non-speech. Traditional audio scene analysis research puts more emphasis on the classification of audio signals into human speech, music, and environmental sounds. We take a different perspective in this paper. We are mainly interested in the analysis of non-speech human sounds, including laugh, screaming, sneeze, and snore. Toward...
An automatic diagnosis system of nuclear cataract is presented in this paper. Nuclear cataract is graded according to the severity of opacity using slit-lamp lens images. Anatomical structure in the lens image is detected using a modified active shape model (ASM). Based on the anatomical landmark, local features are extracted according to clinical grading protocol. Support vector machine (SVM) regression...
Maximum likelihood linear regression (MLLR) is a widely used technique for speaker adaptation in large vocabulary speech recognition system. Recently, using MLLR transforms as features for SVM based speaker recognition tasks has been proposed, achieving performance comparable to that obtained with cepstral features. In this paper, we focus on calculating the transforms based on a GMM universal background...
The method of fault diagnosis of rolling bearings based on wavelet packet transform and support vector machine is presented. The key to fault bearings diagnosis is feature extracting and feature classifying. Wavelet packet transform, as a new technique of signal processing, possesses excellent characteristic of time-frequency localization and is suitable for analyzing the time-varying or transient...
The advent of wearable sensors like accelerometers has opened a plethora of opportunities to recognize human activities from other low resolution sensory streams. In this paper we formulate recognizing activities from accelerometer data as a classification problem. In addition to the statistical and spectral features extracted from the acceleration data, we propose to extract features that characterize...
One particularly difficult challenge for cross-channel MLLR (CMLLR) are two widely-used techniques for speaker introduced in the 2005 and 2006 NIST Speaker Recognition Evaluations, where training uses telephone speech and verification uses speech from multiple auxiliary comparable to that obtained with cepstral features. This paper describes a new feature extraction technique for speaker recognition...
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